Can unnecessary hospitalizations be avoided?

It is said that the best savings in health is in avoidable hospitalisation that doesn’t occur, especially since the use of a hospital bed is the most expensive health resource of all the health offers, but also because if one person, let’s imagine an elderly one with several chronic conditions, can avoid being admitted in hospital, his/her health will suffer less compromising situations. For this reason, all health systems are very active in trying to launch all kinds of measures to reduce the admission of chronic and frail patients.

Dr. Sara Purdy, family physician and Senior Consultant at the University of Bristol, published under the auspices of the King’s Fund, in late 2010, an analysis of what actions reduce the unnecessary hospital admissions and which ones do not. The work of Dr. Purdy is focused only on organisational actions such as home hospitalisation or case management, and, in contrast, does not include strictly clinical factors such as the impact of a new drug for asthma conditions.

See below what actions have been proven to reduce unnecessary hospitalisations (for the source of evidence, consult the King’s Fund paper):

"The Poverty Hypothesis" versus "The Capacity Hypothesis"

The socioeconomic status influences the consumption of goods and services in each community in a very obvious way, a phenomenon which logically includes hospitalisation rates. But in what sense does poverty or wealth determine hospital utilisation? And what role does the accessibility to the number of installed beds in the community play in hospitalisation rates?

To try to answer these two questions I will examine two projects, an English one and an American one that emphasise two different hypothesis, the first one being based on the influence of poverty and the second one, on the installed capacity.

The English analysis. Hypothesis: poverty is crucial

This paper uses as a clinical measure, a closed list of 19 "Ambulatory Care-Sensitive Conditions (ACSC )", such as heart failure or diabetes complications that should not be a reason for admission if primary care had the capacity to globally treat these patients. Regarding the assessment of poverty, the study uses a socioeconomic quintiles index measuring various deprivations (Index of Multiple Deprivations: IMD 2010).

"The Surgical Signature" and how the patients can influence the overtreatment

In his latest book, Tracking Medicine, presented in the first post of this blog, Wennberg says that it’s possible to recognize a hospital by their rates of interventions profile (population-based) from a small handful of surgical procedures. And he demonstrates it with the following graph:

The analysis of the 5 selected areas in this 1975 work shows the profile of five surgical procedures ("The Surgical Signature") of each of them. So you can see that the men of Portland have the highest probability of the series to be undergoing prostatectomy (50% above the average), while citizens of the same Portland, in general, have the lower odds of having haemorrhoidectomy (40% below the average), Lewiston women face the highest rates of hysterectomy (60% above), in Augusta the average varicose extractions doubles, Waterville is the champion in operating haemorrhoids (nearly triples average) and finally the Bangor area is only notable for having the lowest rates of prostatectomy’s series.

The paper concludes that variations in the use of surgical resources are observed not only in comparisons between systems (see previous post) but also, the phenomenon has a land mark that does not correspond with the socio-demographic characteristics (which are adjusted) nor with the prevalence of diseases susceptible to surgical intervention.

Preference sensitive health care: the causes of variations

There is a case-mix part (25% according to Wennberg) such as inguinal hernia, cataracts, metrorrhagia or knee osteoarthritis, for which modern medicine has an effective surgical response, although in the application of the technique there is often a margin for the doctor’s interpretation, another margin for the subjectivity of the patient, such as pain perception or adaptation to the lack of visual acuity, as well as a very important factor: the decision of the patient himself. There are men who prefer to wear a brace to hernia surgery and women who prefer to live with their uterus, provided that the degree of the discomfort and metrorrhagy allows them to.

After this introduction, let’s see the Variations in Health Care, the good, the bad and the inexplicable report by John Appleby and his collaborators, published by King's Fund in 2011, which states that variations in hospitalization rates are pervasive and persistent, and even affect common interventions known to be effective such as hip replacement for advanced osteoarthritis cases.

                Distribution rates of hip replacement in England 2009/10

The cost/effectiveness of successful clinical actions

In this second post I want to talk about health care that is considered to be truly effective, despite the fact that it should be noted that there are effective actions not without controversy in their application in the community. At this point I think it’s appropriate to introduce a metric known as QALY (Quality Adjusted Life Year).

What is a QALY?

A QALY is a unit that measures the cost attributable for each year of added life that healthcare intervention is supposed to bring. In the NICE website (National Health and Clinical Excellence, a English National Health Service Agency which supports the health system to provide the best possible care with the best available evidence) there is a suitable explanation for non-epidemiologists on how to calculate a QALY.

How a QALY is calculated Patient x has a serious, life-threatening condition. • If he continues receiving standard treatment he will live for 1 year and his quality of   life will be 0.4 (0 or below = worst possible health, 1= best possible health) • If he receives the new drug he will live for 1 year 3 months (1.25 years),    with a quality of life of 0.6.  The new treatment is compared with standard care in terms of the QALYs gained: • Standard treatment: 1 (year's extra life) x 0.4 = 0.4 QALY • New treatment: 1.25 (1 year, 3 months extra life) x 0.6 = 0.75 QALY   Therefore, the new treatment leads to 0.35 additional QALYs   (that is: 0.75 -0.4 QALY = 0.35 QALYs). • The cost of the new drug is assumed to be £10,000, standard treatment costs £3000.   The difference in treatment costs (£7000) is divided by the QALYs gained (0.35) to      calculate the cost  per QALY. So the  new treatment would cost £20,000 per QALY.

I think the NICE explanation is very educational (in fact I haven’t found a better one) and can be a good reminder for everyone.

Blog presentation and first delivery (John Wennberg)

The purpose of this blog is to share with colleagues beyond the formative meetings, the advances in clinical management occurring in the world. Or perhaps it would be more appropriate to talk about the findings that I might be able to come across, or those that the blog readers may provide, thus turning this forum into something useful and entertaining.

To start the blog, I would like to discuss the categories of health care issues that John Wennberg describes in his latest book, a magnificent collection of the research work undertaken during his long career.

The first Wennberg category would be the unquestionably effective health care, such as most immunizations or many of the preventive interventions proven by their good results. According to the author, this group of health activity represents 15% of the total and in this category; health care systems should ensure the accessibility of the population to these facilities and logically, should fight the tendency of low usage of these services by the most disadvantaged people.